In order to reconstruct a color image it is necessary to carry out an operation known as color interpolation (or demosaicing) such to generate triplets of base color values (RGB) or more values, one for each base hue, through appropriate interpolation algorithms for generating values of missing colors for each image pixel.
Numerous techniques for processing data provided by a digital color sensor have been proposed. It is worth mentioning the following documents:    [1] M. R. Gupta, T. Chen, “Vector Color Filter Array Demosaicing” SPIE Electronic Imaging 2001;    [2] R. Ramanath, W. E. Snyder, G. L. Bilbro, W. A. Sander, “Demosaicing Methods for Bayer Color Arrays”, Journal of Electronic Imaging, vol. 11, n. 3, pages 306-315, July 2002;    [3] R. Kimmel, “Demosaicing: Image Reconstruction from Color CCD Samples”;    [4] R. Kakarala, Z. Baharav, “Adaptive Demosaicing with The Principal Vector Method”, IEEE Transactions on Consumer Electronics, vol. 48, n. 4, pages 932-937, November 2002;    [5] B. E. Bayer, “Color Imaging Array”, U.S. Pat. No. 3,971,065, July 1976;    [6] B. K. Gunturk, Y. Altunbasak, R, Mersereau, “Color Plane Interpolation Using Alternating Projections”, IEEE Transactions on Image Processing, vol. 11, no. 9, pages 997-1013, September 2002;    [7] Lanlan Chang and Yap-Peng Tan, “Effective use of Spatial and Spectral Correlations for Color Filter Array Demosaicking”, IEEE Transactions on Consumer Electronics, Vol. 50, No. 1, pages 355-365, February 2004.    [8] Ed Chang, Shiufun Cheung and Davis Pan, “Color Filter Array Recovery Using a Threshold-based Variable Number of Gradients”, Proc. SPIE, vol. 3650, pp. 36-43, 1999.    [9] G. Messina, M. Guarnera, V. Tomaselli, A. Bruna, G. Spampinato, A. Castorina, “Color interpolation method of an image acquired by a digital sensor by directional filtering”, U.S. Patent Application Publication No. 2006072814, April 2006.    [10] S. Smith, “Color image restoration with anti-alias”, U.S. Pat. No. 6,842,191.
Many known techniques preliminarily subdivide the image data stream generated by the digital color sensor in two or more channels, in three channels for the case of a filtering based upon the RGB triplet of primary colors (red, green, blue), as shown in FIG. 1. When the red component of a pixel is to be estimated, but only its green level has been acquired, it is necessary to estimate the red pixels adjacent to the considered pixel, and so on, when the value of another missing color is to be estimated.
The color interpolation step drastically influences the quality of the whole image generation pipeline and it may produce artifacts.
Clearly, subdividing in different channels grey level data generated by the digital color sensor and the successive merging operation of the values calculated for primary colors or base hues with the known value of the primary color of base hue for the considered pixel implies an evident computational burden or, in case of hardware implementation, an increased circuit complexity.
A wide variety of papers and patents has been produced about color interpolation techniques. Among them, there are non adaptive (linear, cubic, etc.) and adaptive (edge sensing) solutions. Adaptive methods usually outperform non adaptive ones, producing more visually pleasant results, less affected by false colors and zipper effect.
The demand of new consumer applications of digital photo-cameras and similar devices, for instance in cellular phones, in laptop (notebook) or hand-held computers and other devices for mobile communications, forces to devise even more effective and at the same time low cost techniques for processing images acquired by a digital color sensor. A particular important requisite is the low cost, because these techniques must be used in devices economically accessible to single consumers.